Classification of juices and fermented beverages made from unripe, ripe and senescent apples based on the aromatic profile using chemometrics

Braga, Cíntia Maia; Zielinski, Acácio Antônio Ferreira; Silva, Karolline Marques da; Souza, Frederico Koch Fernandes de; Pietrowski, Giovana de Arruda Moura; Couto, Marcelo; Granato, Daniel; Wosiacki, Gilvan; Nogueira, Alessandro

doi:10.1016/j.foodchem.2013.04.007

Cited by 72 publications

(56 citation statements)

References 34 publications

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“…A fermentation time of 12 d for cider is sufficient for total sugar consumption by the yeast at a temperature higher than 20 °C and nitrogen content above 75 mg/L (Alberti and others ; Braga and others ). However, all the treatments involving alcoholic fermentation were stopped after 10 d, interrupting the fermentation before the complete consumption of sugars to avoid consumption or changes in the volatile profile and amino acid release by yeast autolysis (Alcaide‐Hidalgo and others ).…”

Section: Resultsmentioning

confidence: 99%

“…A multivariate approach composed of hierarchical cluster analysis (HCA) was employed to analyze the experimental results and to try to associate the amino acids with the volatile compounds. For this purpose, the variables were autoscaled using the z ‐score method, where each element of the data matrix was mean‐centered and scaled to a variance of one (Braga and others ). A data matrix composed of samples ( n = 8) and variables ( n = 34) was used, totaling 272 data points.…”

Section: Methodsmentioning

confidence: 99%

“…Various volatile compounds of different classes have been found in ciders, mainly higher alcohols, esters, fatty acids, and aromatic compounds such as 2‐phenylethanol (Xu and others ; Peng and others ; Rita and others ; Fan and others ; Braga and others ; Ye and others ; Haider and othres ). Some of these are derived from the fruit and are typical of the cultivar (ethyl butanoate and hexyl ethanoate) but most are formed during alcoholic fermentation as secondary metabolites (Xu and others ; Madrera and Mangas ).…”

Section: Introductionmentioning

confidence: 99%

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Apple Aminoacid Profile and Yeast Strains in the Formation of Fusel Alcohols and Esters in Cider Production

Santos

Pietrowski

Braga

et al. 2015

Journal of Food Science

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The amino acid profile in dessert apple must and its effect on the synthesis of fusel alcohols and esters in cider were established by instrumental analysis. The amino acid profile was performed in nine apple musts. Two apple musts with high (>150 mg/L) and low (<75 mg/L) nitrogen content, and four enological yeast strains, were used in cider fermentation. The aspartic acid, asparagine and glutamic acid amino acids were the majority in all the apple juices, representing 57.10% to 81.95%. These three amino acids provided a high consumption (>90%) during fermentation in all the ciders. Principal component analysis (PCA) explained 81.42% of data variability and the separation of three groups for the analyzed samples was verified. The ciders manufactured with low nitrogen content showed sluggish fermentation and around 50% less content of volatile compounds (independent of the yeast strain used), which were mainly 3-methyl-1-butanol (isoamyl alcohol) and esters. However, in the presence of amino acids (asparagine, aspartic acid, glutamic acid and alanine) there was a greater differentiation between the yeasts in the production of fusel alcohols and ethyl esters. High contents of these aminoacids in dessert apple musts are essential for the production of fusel alcohols and most of esters by aromatic yeasts during cider fermentation.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Apple Aminoacid Profile and Yeast Strains in the Formation of Fusel Alcohols and Esters in Cider Production

Santos

Pietrowski

Braga

et al. 2015

Journal of Food Science

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“…HCA was performed with autoscaled data. The similarities between the samples were calculated based on the square of the Euclidean distance, and the clusters were defined by the Ward hierarchic agglomeration method (Braga et al, 2013). In order to compare the results of the sample groups (Cluster 1, Cluster 2, and Cluster 3) found in the HCA, the data were initially evaluated using the Shapiro-Wilk test to prove normality, followed by the Levene test to prove variance homogeneity, and finally the Fisher test (when variance homogeneity was confirmed) or the Kruskall-Wallis test (when variance homogeneity was not confirmed) were applied.…”

Section: Discussionmentioning

confidence: 99%

Quality evaluation of parmesan-type cheese: a chemometric approach

Jaster¹,

Campos²,

Auer³

et al. 2014

Food Sci. Technol (Campinas)

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“…Not only because of financial reasons, the sensory characteristics, chemical composition, and authenticity of juices, here namely as typicality, could be assessed through analytical measurements. Some of the analytical techniques widely used to evaluate the quality of fruit juices include gas chromatography, routine analysis of nutritional composition, instrumental color, and high‐performance liquid chromatography (HPLC) of phenolic compounds, carotenoids, and some vitamins, among others (Obón and others ; Braga and others ). However, other techniques can also be employed to evaluate commercial fruit juices, such as sensory analysis using consumers and/or a trained taste panel or even by using an instrumental taste sensing system, the electronic tongue (Campos and others ; Wang and Qiu ; Granato and others , ).…”

Section: Introductionmentioning

confidence: 99%

Characterization of Conventional, Biodynamic, and Organic Purple Grape Juices by Chemical Markers, Antioxidant Capacity, and Instrumental Taste Profile

Granato

Margraf

Brotzakis

et al. 2014

Journal of Food Science

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The objectives of this study were to characterize organic, biodynamic, and conventional purple grape juices (n = 31) produced in Europe based on instrumental taste profile, antioxidant activity, and some chemical markers and to propose a multivariate statistical model to analyze their quality and try to classify the samples from the 3 different crop systems. Results were subjected to ANOVA, correlation, and regression analysis, principal component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogy (SIMCA), and partial least-squares discriminant analysis (PLSDA). No statistical significant differences (P > 0.05) were observed among juices from the 3 crop systems. Using PCA and HCA, no clear separation among crop systems was observed, corroborating the ANOVA data. However, PCA showed that the producing region highly affects the chemical composition, electronic tongue parameters, and bioactivity of grape juices. In this sense, when organic and biodynamic were grouped as "nonconventional" juices, SIMCA model was able to discriminate 12 out of 13 organic/biodynamic juices and 17 out of 18 conventional juices, presenting an efficiency of 93.5%, while 11 out of 13 non-conventional and 100% conventional grape juices were correctly classified using PLSDA. The use of electronic tongue and the determination of antioxidant properties and major phenolic compounds have shown to be a quick and accurate analytical approach to assess the quality of grape juices.

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Classification of juices and fermented beverages made from unripe, ripe and senescent apples based on the aromatic profile using chemometrics

Cited by 72 publications

References 34 publications

Apple Aminoacid Profile and Yeast Strains in the Formation of Fusel Alcohols and Esters in Cider Production

Apple Aminoacid Profile and Yeast Strains in the Formation of Fusel Alcohols and Esters in Cider Production

Quality evaluation of parmesan-type cheese: a chemometric approach

Characterization of Conventional, Biodynamic, and Organic Purple Grape Juices by Chemical Markers, Antioxidant Capacity, and Instrumental Taste Profile

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